AgentIndex icon
AgentIndex
crg logo
crg
★ 76
vs
deep-research logo
deep-research
★ 4.7k

crg vs deep-research

crg: `crg` (formerly `better-code-review-graph`) is a local-first knowledge graph tool for codebases, enabling token-efficient code reviews through semantic search, call-graph resolution, and structural analysis. It integrates with AI agents via MCP for precise context provision, leveraging local ONNX embeddings or cloud models for enhanced code understanding and security scanning.; deep-research: Deep Research is an AI-powered tool designed to generate comprehensive research reports rapidly, leveraging advanced AI models and internet connectivity. It prioritizes user privacy by processing and storing all data locally.

01

TL;DR

crg logo
crgRAG / Knowledge Base · ★ 76

Performing token-efficient code reviews with precise context for AI agents

Read crg full review →
deep-research logo
deep-researchRAG / Knowledge Base · ★ 4.7k

Rapidly generate in-depth research reports for personal and professional use.

Read deep-research full review →
02

Side-by-Side Comparison

Field
crg logocrg
deep-research logodeep-research
Category
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 76
★ 4.7k
License
Apache-2.0
MIT
Install Command
pip install better-code-review-graph
docker run -d --name deep-research -p 3333:3000 xiangfa/deep-research
Updated
1d ago
4mo ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
Knowledge Graph, Code Review, Semantic Search
AI Research, LLM, Privacy-focused
03

Features

crg logocrg
01AND-logic multi-word search for code entities
02Qualified call graph resolution and bare fallback
03Dual-mode fastretrieval ONNX and cloud embeddings (Jina/Gemini/OpenAI/Cohere)
04Paginated and truncated output for large search results
05Integrated security scanning with Semgrep and heuristic rules
deep-research logodeep-research
01Rapidly generates comprehensive research reports in minutes.
02Ensures privacy by processing and storing all data locally in the browser.
03Supports a wide range of mainstream large language models (LLMs).
04Integrates with various web search engines for enhanced information gathering.
05Allows uploading and processing local files to build a knowledge base.
04

Use Cases

crg logocrg
↳Performing token-efficient code reviews with precise context for AI agents
↳Conducting semantic search and call-graph resolution across a codebase
↳Analyzing the blast radius and impact of changed files within a repository
↳Running local security scans on code using heuristic rules or Semgrep engine
↳Onboarding new repositories and quickly understanding code structure and relationships
deep-research logodeep-research
↳Rapidly generate in-depth research reports for personal and professional use.
↳Serve as a deep research as a service (SaaS) platform via SSE API.
↳Integrate deep research functionality into other AI applications using MCP.
FAQ

FAQ

What is the difference between crg and deep-research?
Both crg and deep-research are in the RAG / Knowledge Base category. crg has 76 stars, while deep-research has 4.7k stars.
Which is better, crg or deep-research?
The best choice depends on your use case. Choose crg if Performing token-efficient code reviews with precise context for AI agents, and deep-research if Rapidly generate in-depth research reports for personal and professional use..
Is crg free or open source?
Yes, crg is open source on GitHub (Apache-2.0).
Is deep-research free or open source?
Yes, deep-research is open source on GitHub (MIT).
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